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Objectives This study aimed to comprehensively characterise genetic variants of amelogenesis imperfecta in a single Korean family through whole-exome sequencing and bioinformatics analysis. Material and methods Thirty-one individuals of a Korean family, 9 of whom were affected and 22 unaffected by amelogenesis imperfecta, were enrolled. Whole-exome sequencing was performed on 12 saliva samples, including samples from 8 affected and 4 unaffected individuals. The possible candidate genes associated with the disease were screened by segregation analysis and variant filtering. In silico mutation impact analysis was then performed on the filtered variants based on sequence conservation and protein structure. Results Whole-exome sequencing data revealed an X-linked dominant, heterozygous genomic missense mutation in the mitochondrial gene holocytochrome c synthase (HCCS). We also found that HCCS is potentially related to the role of mitochondria in amelogenesis. The HCCS variant was expected to be deleterious in both evolution-based and large population-based analyses. Further, the variant was predicted to have a negative effect on catalytic function of HCCS by in silico analysis of protein structure. In addition, HCCS had significant association with amelogenesis in literature mining analysis. Conclusions These findings suggest new evidence for the relationship between amelogenesis and mitochondria function, which could be implicated in the pathogenesis of amelogenesis imperfecta. Clinical relevance The discovery of HCCS mutations and a deeper understanding of the pathogenesis of amelogenesis imperfecta could lead to finding solutions for the fundamental treatment of this disease. Furthermore, it enables dental practitioners to establish predictable prosthetic treatment plans at an early stage by early detection of amelogenesis imperfecta through personalised medicine.

Immune checkpoint inhibitors (ICIs) have substantially improved the survival of cancer patients over the past several years. However, only a minority of patients respond to ICI treatment (~30% in solid tumors), and current ICI-response-associated biomarkers often fail to predict the ICI treatment response. Here, we present a machine learning (ML) framework that leverages network-based analyses to identify ICI treatment biomarkers (NetBio) that can make robust predictions. We curate more than 700 ICI-treated patient samples with clinical outcomes and transcriptomic data, and observe that NetBio-based predictions accurately predict ICI treatment responses in three different cancer types—melanoma, gastric cancer, and bladder cancer. Moreover, the NetBio-based prediction is superior to predictions based on other conventional ICI treatment biomarkers, such as ICI targets or tumor microenvironment-associated markers. This work presents a network-based method to effectively select immunotherapy-response-associated biomarkers that can make robust ML-based predictions for precision oncology.

Invariant natural killer T (iNKT), mucosal-associated invariant T (MAIT), and γδ T cells are innate T cells that acquire memory phenotype in the thymus and share similar biological characteristics. However, how their effector differentiation is developmentally regulated is still unclear. Here, we identify analogous effector subsets of these three innate T cell types in the thymus that share transcriptional profiles. Using single-cell RNA sequencing, we show that iNKT, MAIT and γδ T cells mature via shared, branched differentiation rather than linear maturation or TCR-mediated instruction. Simultaneous TCR clonotyping analysis reveals that thymic maturation of all three types is accompanied by clonal selection and expansion. Analyses of mice deficient of TBET, GATA3 or RORγt and additional in vivo experiments corroborate the predicted differentiation paths, while human innate T cells from liver samples display similar features. Collectively, our data indicate that innate T cells share effector differentiation processes in the thymus., Innate T cells such as iNKT, MAIT and γδ T cells all develop in the thymus, but their differentiation paths are still unclear. Here, the authors show, using single-cell RNA sequencing, that all three cell types develop via shared and branched differentiation paths that are corroborated by additional results from gene-deficient mice and human liver T cells.

Cancer stem cells (CSCs) play a central role in cancer initiation, progression, therapeutic resistance, and recurrence in patients. Here we present Capicua (CIC), a developmental transcriptional repressor, as a suppressor of CSC properties in breast cancer cells. CIC deficiency critically enhances CSC self-renewal and multiple CSC subpopulations of breast cancer cells without altering their growth rate or invasiveness. Loss of CIC relieves repression of ETV4 and ETV5 expression, consequently promoting self-renewal capability, EpCAM+/CD44+/CD24low/- expression, and ALDH activity. In xenograft models, CIC deficiency significantly increases CSC frequency and drives tumor initiation through derepression of ETV4. Consistent with the experimental data, the CD44high/CD24low CSC-like feature is inversely correlated with CIC levels in breast cancer patients. We also identify SOX2 as a downstream target gene of CIC that partly promotes CSC properties. Taken together, our study demonstrates that CIC suppresses breast cancer formation via restricting cancer stemness and proposes CIC as a potential regulator of stem cell maintenance.

Within a protein family, proteins with the same domain often exhibit different cellular functions, despite the shared evolutionary history and molecular function of the domain. We hypothesized that domain-mediated interactions (DMIs) may categorize a protein family into subfamilies because the diversified functions of a single domain often depend on interacting partners of domains. Here we systematically identified DMI subfamilies, in which proteins share domains with DMI partners, as well as with various functional and physical interaction networks in individual species. In humans, DMI subfamily members are associated with similar diseases, including cancers, and are frequently co-associated with the same diseases. DMI information relates to the functional and evolutionary subdivisions of human kinases. In yeast, DMI subfamilies contain proteins with similar phenotypic outcomes from specific chemical treatments. Therefore, the systematic investigation here provides insights into the diverse functions of subfamilies derived from a protein family with a link-centric approach and suggests a useful resource for annotating the functions and phenotypic outcomes of proteins.

Recent studies have shown that many essential genes (EGs) change their essentiality across various contexts. Finding contextual EGs in pathogenic conditions may facilitate the identification of therapeutic targets. We propose link clustering as an indicator of contextual EGs that are non-central in protein-protein interaction (PPI) networks. In various human and yeast PPI networks, we found that 29–47% of EGs were better characterized by link clustering than by centrality. Importantly, non-central EGs were prone to change their essentiality across different human cell lines and between species. Compared with central EGs and non-EGs, non-central EGs had intermediate levels of expression and evolutionary conservation. In addition, non-central EGs exhibited a significant impact on communities at lower hierarchical levels, suggesting that link clustering is associated with contextual essentiality, as it depicts locally important nodes in network structures.

Cancer patient classification using predictive biomarkers for anti-cancer drug responses is essential for improving therapeutic outcomes. However, current machine-learning-based predictions of drug response often fail to identify robust translational biomarkers from preclinical models. Here, we present a machine-learning framework to identify robust drug biomarkers by taking advantage of network-based analyses using pharmacogenomic data derived from three-dimensional organoid culture models. The biomarkers identified by our approach accurately predict the drug responses of 114 colorectal cancer patients treated with 5-fluorouracil and 77 bladder cancer patients treated with cisplatin. We further confirm our biomarkers using external transcriptomic datasets of drug-sensitive and -resistant isogenic cancer cell lines. Finally, concordance analysis between the transcriptomic biomarkers and independent somatic mutation-based biomarkers further validate our method. This work presents a method to predict cancer patient drug responses using pharmacogenomic data derived from organoid models by combining the application of gene modules and network-based approaches., Cancer patient classification using predictive biomarkers for anti-cancer drug responses is essential for improving therapeutic outcomes. Here, the authors present a machine-learning framework to identify robust drug biomarkers by taking advantage of network-based analyses using pharmacogenomic data.

Mice have been widely used as a model organism to investigate human gene-phenotype relationships based on a conjecture that orthologous genes generally perform similar functions and are associated with similar phenotypes. However, phenotypes associated with orthologous genes often turn out to be quite different between human and mouse. Herein, we devised a method to quantitatively compare phenotypes annotations associated with mouse models and human. Using semantic similarity comparisons, we identified orthologous genes with different phenotype annotations, of which the similarity score is on a par with that of random gene pairs. Analysis of sequence evolution and transcriptomic changes revealed that orthologous genes with phenotypic differences are correlated with changes in noncoding regulatory elements and tissue-specific expression profiles rather than changes in protein-coding sequences. To map accurate gene-phenotype relationships using model organisms, we propose that careful consideration of the evolutionary divergence of noncoding regulatory elements and transcriptomic profiles is essential.

Sjogren's syndrome (SS), a chronic autoimmune disease, typically causes or involves inflammation in the salivary and lacrimal glands. Although recent genetic association studies have contributed to the discovery of SS susceptible genes, few studies have reported on the Korean population. Here, we did a genetic association study of SS in Korean patients using whole-exome sequencing data of 15 patients and 100 healthy controls. In addition to confirming previously described SS susceptibility loci MSH5 (p = 1.67 × 10–5) and RELN (p = 4.91 × 10–6), we also validated PRAMEF13 (p = 2.28 × 10–5), TARBP1 (p = 1.87 × 10–5), UGT2B28 (p = 1.33 × 10–5), TRBV5-6 (p = 2.27 × 10–5) and NAPB (p = 3.73 × 10–5) as novel susceptibility loci for SS. Furthermore, we identified UGT2B28, TARBP1 and PRAMEF13 as associated with human immune function. These findings may provide useful insight into to the pathways and pathogenesis contributing to SS susceptibility in the Korean population.

Objectives Our study aims to identify genetic variants associated with hereditary gingival fibromatosis (HGF) by applying whole exome sequencing (WES) and bioinformatics analyses such as gene set enrichment analysis (GSEA) and protein functional network study. Subjects and Methods Two affected siblings whose grandparents and parents have normal gingiva were chosen for our investigation. Saliva collected from the patients and their parents were used for WES. GSEA and protein functional network study were performed to find gene groups in a biological coordination which are associated with HGF. Results Genetic variants for homozygotes and compound heterozygotes were analyzed and translated into 845 genes. The result from protein functional network study showed that these genetic variants were mainly observed in genes affecting fibronectin as well as the immune and auto-immune system. Additionally, three mutated genes in our HGF patients, TMCO1, RIN2, and INSR,were found through human phenotype ontology (HPO) to have potential to contribute to gingival hyperplasia. Conclusions Genetic analysis of HGF in this study implicated mutations in fibronectin and the immune system as triggering abnormal gingival fibromatosis. This article is protected by copyright. All rights reserved.

Objective Hereditary gingival fibromatosis (HGF) is a rare oral disease characterized by either localized or generalized gradual, benign, non-hemorrhagic enlargement of gingivae. Although several genetic causes of HGF are known, the genetic etiology of HGF as a non-syndromic and idiopathic entity remains uncertain. Subjects and methods We performed exome and RNA-seq of idiopathic HGF patients and controls, and then devised a computational framework that specifies exomic/transcriptomic alterations interconnected by a regulatory network to unravel genetic etiology of HGF. Moreover, given the lack of animal model or large-scale cohort data of HGF, we developed a strategy to cross-check their clinical relevance through in silico gene-phenotype mapping with biomedical literature mining and semantic analysis of disease phenotype similarities. Results Exomic variants and differentially expressed genes of HGF were connected by members of TGF-β/SMAD signaling pathway and craniofacial development processes, accounting for the molecular mechanism of fibroblast overgrowth mimicking HGF. Our cross-check supports that genes derived from the regulatory network analysis have pathogenic roles in fibromatosis-related diseases. Conclusions The computational approach of connecting exomic and transcriptomic alterations through regulatory networks is applicable in the clinical interpretation of genetic variants in HGF patients.

In bladder, loss of mammalian Sonic Hedgehog (Shh) accompanies progression to invasive urothelial carcinoma, but the molecular mechanisms underlying this cancer-initiating event are poorly defined. Here, we show that loss of Shh results from hypermethylation of the CpG shore of the Shh gene, and that inhibition of DNA methylation increases Shh expression to halt the initiation of murine urothelial carcinoma at the early stage of progression. In full-fledged tumors, pharmacologic augmentation of Hedgehog (Hh) pathway activity impedes tumor growth, and this cancer-restraining effect of Hh signaling is mediated by the stromal response to Shh signals, which stimulates subtype conversion of basal to luminal-like urothelial carcinoma. Our findings thus provide a basis to develop subtype-specific strategies for the management of human bladder cancer., eLife digest In order to grow, cancer cells shut down or over-activate genes that normally maintain a cell’s health. The Sonic Hedgehog gene – named after a Japanese cartoon character – is associated with the cancer of several tissues, including the bladder. In 2014, researchers found that losing the Sonic Hedgehog gene, Shh for short, is necessary for bladder cancers to become aggressive: Shh signals prompt healthy cells near the tumor to inhibit the cancer cell growth, whilst aggressive bladder cancer cells turn off the Shh gene. Kim et al. – including many of the researchers involved in the 2014 work – now investigate how cancer cells switch off the Shh gene and what effect it has on bladder cancer cells and their surrounding tissue when turned back on. DNA sequencing bladder cancer cells derived from human patients showed that there were no genetic deletions or mutations within the gene. However, the sequence and nearby regions of DNA did contain methylations – a chemical modification that generally switches genes off. When mice with early stages of bladder cancer were treated with a drug that inhibits methylation, the Shh gene turned back on, the bladder cancers stopped growing and the tumors stayed at an early stage of development. When the same drug was used on mice with aggressive bladder cancer, this caused non-cancer cells in the surrounding tissue to respond to Shh and send restraining signals back to the tumor. These signals eventually stopped cancer growth and converted the tumor into a less aggressive type of bladder cancer. Additionally, Kim et al. saw that blocking methylation had the same effect on human bladder cancer cells that had been transplanted into mice. These results therefore indicate that Shh could be a new target for cancer treatments. For instance, drugs that decrease methylation and turn on the gene could be a way of managing cancer in patients with aggressive bladder cancers, which often show low activity of the gene. However, future studies are needed to understand what exactly happens within cancer cells during tumor conversion and to determine if this kind of intervention could have unintended consequences.

Hepatocellular carcinoma (HCC) is developed by multiple steps accompanying progressive alterations of gene expression, which leads to increased cell proliferation and malignancy. Although environmental factors and intracellular signaling pathways that are critical for HCC progression have been identified, gene expression changes and the related genetic factors contributing to HCC pathogenesis are still insufficiently understood. In this study, we identify a transcriptional repressor, Capicua (CIC), as a suppressor of HCC progression and a potential therapeutic target. Expression of CIC is posttranscriptionally reduced in HCC cells. CIC levels are correlated with survival rates in patients with HCC. CIC overexpression suppresses HCC cell proliferation and invasion, whereas loss of CIC exerts opposite effects in vivo as well as in vitro. Levels of polyoma enhancer activator 3 (PEA3) group genes, the best-known CIC target genes, are correlated with lethality in patients with HCC. Among the PEA3 group genes, ETS translocation variant 4 (ETV4) is the most significantly up-regulated in CIC-deficient HCC cells, consequently promoting HCC progression. Furthermore, it induces expression of matrix metalloproteinase 1 (MMP1), the MMP gene highly relevant to HCC progression, in HCC cells; and knockdown of MMP1 completely blocks the CIC deficiency-induced HCC cell proliferation and invasion. Conclusion Our study demonstrates that the CIC-ETV4-MMP1 axis is a regulatory module controlling HCC progression. (Hepatology 2018;67:2287-2301).

Genome-wide association studies have discovered a large number of genetic variants in human patients with the disease. Thus, predicting the impact of these variants is important for sorting disease-associated variants (DVs) from neutral variants. Current methods to predict the mutational impacts depend on evolutionary conservation at the mutation site, which is determined using homologous sequences and based on the assumption that variants at well-conserved sites have high impacts. However, many DVs at less-conserved but functionally important sites cannot be predicted by the current methods. Here, we present a method to find DVs at less-conserved sites by predicting the mutational impacts using evolutionary coupling analysis. Functionally important and evolutionarily coupled sites often have compensatory variants on cooperative sites to avoid loss of function. We found that our method identified known intolerant variants in a diverse group of proteins. Furthermore, at less-conserved sites, we identified DVs that were not identified using conservation-based methods. These newly identified DVs were frequently found at protein interaction interfaces, where species-specific mutations often alter interaction specificity. This work presents a means to identify less-conserved DVs and provides insight into the relationship between evolutionarily coupled sites and human DVs.

The growth arrest and DNA damage inducible, alpha (Gadd45α) protein regulates DNA repair by interacting with proliferating cell nuclear antigen (PCNA). Our previous study suggested a potential role for Gadd45α in the base excision repair (BER) pathway by affecting apurinic/apyrimidinic endonuclease 1 (APE1) protein in addition to its accepted role in nucleotide excision repair (NER). Here, we investigated whether the interaction of Gadd45α with PCNA affects APE1 activity. To address this issue, we used a siRNA directed to Gadd45α and a form of Gadd45α with a mutation to the predicted site of PCNA binding. There was a reduction of APE1 activity in cells transfected with the Gadd45α siRNA. Furthermore, the interaction of Gadd45α with PCNA and APE1 was lower in cells transfected with mutant Gadd45α compared with cells transfected with wild-type Gadd45α. Indeed, we observed that the APE1 activity in the Gadd45α-interacting complex was significantly lower in cells that overexpress mutant Gadd45α compared with cells that overexpress wild-type Gadd45α. We conclude that the PCNA binding site on Gadd45α plays a critical role in modulating the interaction with PCNA and APE1, affecting BER activity. These results provide novel insights into the mechanisms by which BER activity is modulated, although the interaction of Gadd45α with APE1 needs to be clarified.

Members of the herpesviral family use multiple strategies to hijack infected host cells and exploit cellular signaling for their pathogenesis and latent infection. Among the most intriguing weapons in the arsenal of pathogenic herpesviruses are the constitutively active virally-encoded G protein-coupled receptors (vGPCRs). Even though vGPCRs contribute to viral pathogenesis such as immune evasion and proliferative disorders, the molecular details of how vGPCRs continuously activate cellular signaling are largely unknown. Here, we report that the vGPCR of Herpesvirus saimiri (HVS), an oncogenic γ2-herpesvirus, constitutively activates T cells via a heteromeric interaction with cellular CXCR4. Constitutive T cell activation also occurs with expression of the vGPCR of Kaposi's sarcoma-associated herpesvirus (KSHV), but not the vGPCR of Epstein-Barr virus. Expression of HVS vGPCR down-regulated the surface expression of CXCR4 but did not induce the degradation of the chemokine receptor, suggesting that vGPCR/CXCR4 signaling continues in cytosolic compartments. The physical association of vGPCR with CXCR4 was demonstrated by proximity ligation assay as well as immunoprecipitation. Interestingly, the constitutive activation of T cells by HVS vGPCR is independent of proximal T cell receptor (TCR) signaling molecules, such as TCRβ, Lck, and ZAP70, whereas CXCR4 silencing by shRNA abolished T cell activation by vGPCRs of HVS and KSHV. Furthermore, previously identified inactive vGPCR mutants failed to interact with CXCR4. These findings on the positive cooperativity of vGPCR with cellular CXCR4 in T cell activation extend our current understanding of the molecular mechanisms of vGPCR function and highlight the importance of heteromerization for GPCR activity.

The newly emerging Middle East respiratory syndrome coronavirus (MERS-CoV) causes a severe respiratory infection with a high mortality rate (~35%). MERS-CoV has been a global threat due to continuous outbreaks in the Arabian peninsula and international spread by infected travelers since 2012. From May to July 2015, a large outbreak initiated by an infected traveler from the Arabian peninsula swept South Korea and resulted in 186 confirmed cases with 38 deaths (case fatality rate, 20.4%). Here, we show the rapid emergence and spread of a mutant MERS-CoV with reduced affinity to the human CD26 receptor during the South Korean outbreak. We isolated 13 new viral genomes from 14 infected patients treated at a hospital and found that 12 of these genomes possess a point mutation in the receptor-binding domain (RBD) of viral spike (S) protein. Specifically, 11 of these genomes have an I529T mutation in RBD, and 1 has a D510G mutation. Strikingly, both mutations result in reduced affinity of RBD to human CD26 compared to wild-type RBD, as measured by surface plasmon resonance analysis and cellular binding assay. Additionally, pseudotyped virus bearing an I529T mutation in S protein showed reduced entry into host cells compared to virus with wild-type S protein. These unexpected findings suggest that MERS-CoV adaptation during human-to-human spread may be driven by host immunological pressure such as neutralizing antibodies, resulting in reduced affinity to host receptor, and thereby impairs viral fitness and virulence, rather than positive selection for a better affinity to CD26., IMPORTANCE Recently, a large outbreak initiated by an MERS-CoV-infected traveler from the Middle East swept South Korea and resulted in 186 confirmed cases with 38 deaths. This is the largest outbreak outside the Middle East, and it raised strong concerns about the possible emergence of MERS-CoV mutations. Here, we isolated 13 new viral genomes and found that 12 of them possess a point mutation in the receptor-binding domain of viral spike protein, resulting in reduced affinity to the human cognate receptor, CD26, compared to the wild-type virus. These unexpected findings suggest that MERS-CoV adaptation in humans may be driven by host immunological pressure.

Online application for survival analysis (OASIS) has served as a popular and convenient platform for the statistical analysis of various survival data, particularly in the field of aging research. With the recent advances in the fields of aging research that deal with complex survival data, we noticed a need for updates to the current version of OASIS. Here, we report OASIS 2 (http://sbi.postech.ac.kr/oasis2), which provides extended statistical tools for survival data and an enhanced user interface. In particular, OASIS 2 enables the statistical comparison of maximal lifespans, which is potentially useful for determining key factors that limit the lifespan of a population. Furthermore, OASIS 2 provides statistical and graphical tools that compare values in different conditions and times. That feature is useful for comparing age-associated changes in physiological activities, which can be used as indicators of "healthspan." We believe that OASIS 2 will serve as a standard platform for survival analysis with advanced and user-friendly statistical tools for experimental biologists in the field of aging research.

Phospholipase C-β (PLC-β) is a key molecule in G protein-coupled receptor (GPCR)-mediated signaling. Many studies have shown that the four PLC-β subtypes have different physiological functions despite their similar structures. Because the PLC-β subtypes possess different PDZ-binding motifs, they have the potential to interact with different PDZ proteins. In this study, we identified PDZ domain-containing 1 (PDZK1) as a PDZ protein that specifically interacts with PLC-β3. To elucidate the functional roles of PDZK1, we next screened for potential interacting proteins of PDZK1 and identified the somatostatin receptors (SSTRs) as another protein that interacts with PDZK1. Through these interactions, PDZK1 assembles as a ternary complex with PLC-β3 and SSTRs. Interestingly, the expression of PDZK1 and PLC-β3, but not PLC-β1, markedly potentiated SST-induced PLC activation. However, disruption of the ternary complex inhibited SST-induced PLC activation, which suggests that PDZK1-mediated complex formation is required for the specific activation of PLC-β3 by SST. Consistent with this observation, the knockdown of PDZK1 or PLC-β3, but not that of PLC-β1, significantly inhibited SST-induced intracellular Ca(2+) mobilization, which further attenuated subsequent ERK1/2 phosphorylation. Taken together, our results strongly suggest that the formation of a complex between SSTRs, PDZK1, and PLC-β3 is essential for the specific activation of PLC-β3 and the subsequent physiologic responses by SST.

Bax Inhibitor-1 (BI-1) is an evolutionally conserved apoptotic suppressor and belongs to the BI-1 family of proteins, which contain BI-1-like transmembrane domains. As their cellular functions and regulatory mechanisms remain incompletely understood, we compared their anti-apoptotic properties. Forced expression of BI-1 resulted in the most effective suppression of stress-induced apoptosis, compared with other family members, together with significant extracellular signal-regulated kinase (ERK)1/2 activation. BI-1-mediated ERK1/2 activation led to the suppression of mitochondria-mediated reactive oxygen species (ROS) production. Involvement of the ERK signaling pathway in BI-1-induced anti-apoptotic effects was confirmed by knockdown studies with ERK- or BI-1-specific siRNA. Moreover, we produced transgenic (TG) mice overexpressing BI-1, and the relationship between ERK1/2 activation and the suppression of ROS production or apoptosis was confirmed in mouse embryonic fibroblast (MEF) cells derived from these mice. Interestingly, we found that BI-1 TG mice showed splenomegaly and abnormal megakaryopoiesis. Taken together, our results suggest that BI-1-induced ERK1/2 activation plays an important role in the modulation of intracellular ROS generation and apoptotic cell death and may also affect autoimmune response.

Protein interfaces are believed to be evolutionarily more conserved than the rest of the protein surface, but this has not been properly verified using a large protein structural set. Furthermore, recent systematic protein interaction analyses have proved that proteins interacting with many partners have multiple interfaces to connect protein interaction networks, which have never taken into account for conservation analysis of protein interface. Here, we studied the evolutionary conservation of protein interfaces using a large-scale dataset of 2646 protein interfaces with the classification of homodimeric/heterodimeric and obligatory/transient interactions, considering all their known multiple interfaces. We found that protein interfaces were indeed more conserved than noninterface surfaces, and the conservation level of protein interfaces increased when multiple interfaces were properly considered. These findings suggest that conservation analysis should be a good descriptor for protein interface identification and protein-protein interaction predictions. We applied this evolutionary feature to filter docking decoys and found that protein interface conservation worked remarkably well in selecting the near-native structures from the large number of generated docking complexes. Moreover, we discovered that a strong correlation exist between protein interface size and protein interface conservation, which could be a useful filter for the prediction of protein-protein interactions.

Characterizing the subcellular localization of a protein provides a key clue for understanding protein function. However, different protein localization prediction programs often deliver conflicting results regarding the localization of the same protein. As the number of available localization prediction programs continues to grow, there is a need for a consensus prediction approach. To address this need, we developed a consensus localization prediction method called ConLoc based on a large-scale, systematic integration of 13 available programs that make predictions for five major subcellular localizations (cytosol, extracellular, mitochondria, nucleus, and plasma membrane). The ability of ConLoc to accurately predict protein localization was substantially better than existing programs. Using ConLoc prediction, we built a localization-guided functional interaction network of the human proteome and mapped known disease associations within this network. We found a high degree of shared disease associations among functionally interacting proteins that are localized to the same cellular compartment. Thus, the use of consensus localization prediction, such as ConLoc, is a new approach for the identification of novel disease associated genes.

Sequence motifs are responsible for ensuring the proper assembly of transmembrane (TM) helices in the lipid bilayer. To understand the mechanism by which the affinity of a common TM-TM interactive motif is controlled at the sequence level, we compared two well characterized GXXXG motif-containing homodimers, those formed by human erythrocyte protein glycophorin A (GpA, high-affinity dimer) and those formed by bacteriophage M13 major coat protein (MCP, low affinity dimer). In both constructs, the GXXXG motif is necessary for TM-TM association. Although the remaining interfacial residues (underlined) in GpA (LIXXGVXXGVXXT) differ from those in MCP (VVXXGAXXGIXXF), molecular modeling performed here indicated that GpA and MCP dimers possess the same overall fold. Thus, we could introduce GpA interfacial residues, alone and in combination, into the MCP sequence to help decrypt the determinants of dimer affinity. Using both in vivo TOXCAT assays and SDS-PAGE gel migration rates of synthetic peptides derived from TM regions of the proteins, we found that the most distal interfacial sites, 12 residues apart (and approximately 18 A in structural space), work in concert to control TM-TM affinity synergistically.

Recent advances in genome sequencing techniques have improved our understanding of the genotype-phenotype relationship between genetic variants and human diseases. However, genetic variations uncovered from patient populations do not provide enough information to understand the mechanisms underlying the progression and clinical severity of human diseases. Moreover, building a high-resolution genotype-phenotype map is difficult due to the diverse genetic backgrounds of the human population. We built a cross-species genotype-phenotype map to explain the clinical severity of human genetic diseases. We developed a data-integrative framework to investigate network modules composed of human diseases mapped with gene essentiality measured from a model organism. Essential and nonessential genes connect diseases of different types which form clusters in the human disease network. In a large patient population study, we found that disease classes enriched with essential genes tended to show a higher mortality rate than disease classes enriched with nonessential genes. Moreover, high disease mortality rates are explained by the multiple comorbid relationships and the high pleiotropy of disease genes found in the essential gene-enriched diseases. Our results reveal that the genotype-phenotype map of a model organism can facilitate the identification of human disease-gene associations and predict human disease progression.

Peri-implantitis is a frequently occurring gum disease linked to multi-factorial traits with various environmental and genetic causalities and no known concrete pathogenesis. The varying severity of peri-implantitis among patients with relatively similar environments suggests a genetic aspect which needs to be investigated to understand and regulate the pathogenesis of the disease. Six unrelated individuals with multiple clusterization implant failure due to severe peri-implantitis were chosen for this study. These six individuals had relatively healthy lifestyles, with minimal environmental causalities affecting peri-implantitis. Research was undertaken to investigate pathogenic genes in peri-implantitis albeit with a small number of subjects and incomplete elimination of environmental causalities. Whole-exome sequencing was performed on collected saliva samples via self DNA collection kit. Common variants with minor allele frequencies (MAF) > = 0.05 from all control datasets were eliminated and variants having high and moderate impact and loss of function were used for comparison. Gene set enrichment analysis was performed to reveal functional groups associated with the genetic variants. 2,022 genes were left after filtering against dbSNP, the 1000 Genomes East Asian population, and healthy Korean randomized subsample data (GSK project). 175 (p-value

The modular architecture of protein-protein interaction (PPI) networks is evident in diverse species with a wide range of complexity. However, the molecular components that lead to the evolution of modularity in PPI networks have not been clearly identified. Here, we show that weak domain-linear motif interactions (DLIs) are more likely to connect different biological modules than strong domain-domain interactions (DDIs). This molecular division of labor is essential for the evolution of modularity in the complex PPI networks of diverse eukaryotic species. In particular, DLIs may compensate for the reduction in module boundaries that originate from increased connections between different modules in complex PPI networks. In addition, we show that the identification of biological modules can be greatly improved by including molecular characteristics of protein interactions. Our findings suggest that transient interactions have played a unique role in shaping the architecture and modularity of biological networks over the course of evolution., Author Summary Modular architecture is important for the evolution of cellular systems. Modular rearrangements facilitate functional innovations and modular insulations provide robustness to perturbations. However, molecular-level understanding of the mechanisms underlying modular network evolution is currently not well understood. Here we show that strong domain-domain interactions (DDIs) and weak domain-linear motif interactions (DLIs) made different contributions to the evolution of the modular architecture of PPI networks. Especially, DLIs mediate between-module interactions, and that their relative abundance has dramatically increased in metazoan species. Linear motifs have been identified as evolutionary interaction switches since subtle amino acid changes can cause the short sequences in linear motifs to appear and disappear. Our results suggest that subtle changes in linear motifs have contributed to the rewiring of functional modules and, consequently, to functional innovations in metazoan species.

We developed a process to produce novel interactions between two previously unrelated proteins. This process selects protein scaffolds and designs protein interfaces that bind to a surface patch of interest on a target protein. Scaffolds with shapes complementary to the target surface patch were screened using an exhaustive computational search of the human proteome and optimized by directed evolution using phage display. This method was applied to successfully design scaffolds that bind to epidermal growth factor receptor (EGFR) domain II, the interface of EGFR dimerization, with high reactivity toward the target surface patch of EGFR domain II. One potential application of these tailor-made protein interactions is the development of therapeutic agents against specific protein targets.

Characterizing the spatial organization of the human mitochondrial proteome will enhance our understanding of mitochondrial functions at the molecular level and provide key insight into protein-disease associations. However, the sub-organellar location and possible association with mitochondrial diseases are not annotated for most mitochondrial proteins. Here, we characterized the functional and spatial organization of mitochondrial proteins by assessing their position in the Mitochondrial Protein Functional (MPF) network. Network position was assigned to the MPF network and facilitated the determination of sub-organellar location and functional organization of mitochondrial proteins. Moreover, network position successfully identified candidate disease genes of several mitochondrial disorders. Thus, our data support the use of network position as a novel method to explore the molecular function and pathogenesis of mitochondrial proteins.

Successful viral infection requires intimate communication between virus and host cell, a process that absolutely requires various host proteins. However, current efforts to discover novel host proteins as therapeutic targets for viral infection are difficult. Here, we developed an integrative-genomics approach to predict human genes involved in the early steps of hepatitis C virus (HCV) infection. By integrating HCV and human protein associations, co-expression data, and tight junction-tetraspanin web specific networks, we identified host proteins required for the early steps in HCV infection. Moreover, we validated the roles of newly identified proteins in HCV infection by knocking down their expression using small interfering RNAs. Specifically, a novel host factor CD63 was shown to directly interact with HCV E2 protein. We further demonstrated that an antibody against CD63 blocked HCV infection, indicating that CD63 may serve as a new therapeutic target for HCV-related diseases. The candidate gene list provides a source for identification of new therapeutic targets.

The extent to which evolutionary changes have impacted the phenotypic relationships among human diseases remains unclear. In this work, we report that phenotypically similar diseases are connected by the evolutionary constraints on human disease genes. Human disease groups can be classified into slowly or rapidly evolving classes, where the diseases in the slowly evolving class are enriched with morphological phenotypes and those in the rapidly evolving class are enriched with physiological phenotypes. Our findings establish a clear evolutionary connection between disease classes and disease phenotypes for the first time. Furthermore, the high comorbidity found between diseases connected by similar evolutionary constraints enables us to improve the predictability of the relative risk of human diseases. We find the evolutionary constraints on disease genes are a new layer of molecular connection in the network-based exploration of human diseases.

PDZ domain-mediated interactions have greatly expanded during metazoan evolution, becoming important for controlling signal flow via the assembly of multiple signaling components. The evolutionary history of PDZ domain-mediated interactions has never been explored at the molecular level. It is of great interest to understand how PDZ domain-ligand interactions emerged and how they become rewired during evolution. Here, we constructed the first human PDZ domain-ligand interaction network (PDZNet) together with binding motif sequences and interaction strengths of ligands. PDZNet includes 1,213 interactions between 97 human PDZ proteins and 591 ligands that connect most PDZ protein-mediated interactions (98%) in a large single network via shared ligands. We examined the rewiring of PDZ domain-ligand interactions throughout eukaryotic evolution by tracing changes in the C-terminal binding motif sequences of the PDZ ligands. We found that interaction rewiring by sequence mutation frequently occurred throughout evolution, largely contributing to the growth of PDZNet. The rewiring of PDZ domain-ligand interactions provided an effective means of functional innovations in nervous system development. Our findings provide empirical evidence for a network evolution model that highlights the rewiring of interactions as a mechanism for the development of new protein functions. PDZNet will be a valuable resource to further characterize the organization of the PDZ domain-mediated signaling proteome., Author Summary Rewiring of interactions is a powerful tool for the evolution of organism complexity. Rewiring among preexisting proteins provides a simple mechanism for the development of new signaling circuits by redirecting information flows without a gain or loss of genes. Particularly, interactions mediated by short linear motifs can be easily changed by mutations during evolution, resulting in a rewiring of interactions. However, how interaction rewiring of linear motif interactions facilitates the emergence of new protein function during evolution is poorly understood. Here, we systematically investigated the rewiring of interactions mediated by PDZ domains, which are one of the most commonly found peptide recognition modules. We found that PDZ domain-ligand interactions are frequently rewired by C-terminal sequence mutations in PDZ ligands during evolution. Especially, rewiring of PDZ domain-ligand interactions was involved in neuronal function development, occurring concurrently with the emergence of vertebrates and suggesting that reorganization of signaling pathways by rewiring PDZ domain-ligand interactions significantly contributed to the evolution of nervous systems in vertebrates. Our findings highlight the rewiring of interactions as an effective means for functional innovation, providing new insight into eukaryotic evolution, which has not been fully explained by only the expansion of protein families.

Various mammalian cells including tumor cells secrete extracellular vesicles (EVs), otherwise known as exosomes and microvesicles. EVs are nanosized bilayered proteolipids and play multiple roles in intercellular communication. Although many vesicular proteins have been identified, their functional interrelationships and the mechanisms of EV biogenesis remain unknown. By interrogating proteomic data using systems approaches, we have created a protein interaction network of human colorectal cancer cell-derived EVs which comprises 1491 interactions between 957 vesicular proteins. We discovered that EVs have well-connected clusters with several hub proteins similar to other subcellular networks. We also experimentally validated that direct protein interactions between cellular proteins may be involved in protein sorting during EV formation. Moreover, physically and functionally interconnected protein complexes form functional modules involved in EV biogenesis and functions. Specifically, we discovered that SRC signaling plays a major role in EV biogenesis, and confirmed that inhibition of SRC kinase decreased the intracellular biogenesis and cell surface release of EVs. Our study provides global insights into the cargo-sorting, biogenesis, and pathophysiological roles of these complex extracellular organelles.

Background Scrub typhus, caused by Orientia tsutsugamushi infection, is one of the main causes of febrile illness in the Asia-Pacific region. Although cell-mediated immunity plays an important role in protection, little is known about the phenotypic changes and dynamics of leukocytes in scrub typhus patients. Methodology/Principal Findings To reveal the underlying mechanisms of immunological pathogenesis, we extensively analyzed peripheral blood leukocytes, especially T cells, during acute and convalescent phases of infection in human patients and compared with healthy volunteers. We observed neutrophilia and CD4+ T lymphopenia in the acute phase of infection, followed by proliferation of CD8+ T cells during the convalescent phase. Massive T cell apoptosis was detected in the acute phase and preferential increase of CD8+ T cells with activated phenotypes was observed in both acute and convalescent phases, which might be associated or correlated with elevated serum IL-7 and IL-15. Interestingly, peripheral Treg cells were significantly down-regulated throughout the disease course. Conclusions/Significance The remarkable decrease of CD4+ T cells, including Treg cells, during the acute phase of infection may contribute to the loss of immunological memory that are often observed in vaccine studies and recurrent human infection., Author Summary Scrub typhus is an acute febrile illness caused by Orientia tsutsugamushi infection. It has been estimated that one billion people are at risk and one million new cases arise each year in Asian-pacific region. Despite of aggressive attempts to develop a prophylactic vaccine against scrub typhus during the last several decades, all approaches have failed to generate long lasting immunity. In addition, little is known about the immunological pathogenesis of scrub typhus. To understand the pathogenic mechanisms of this infectious disease, we extensively analyzed peripheral leukocytes, especially T cells, in Korean scrub typhus patients and compared with healthy volunteers. We observed neutrophilia and CD4+/T lymphopenia in the acute phase of infection, followed by proliferation of CD8+ T cells during the convalescent phase. Massive T cell apoptosis was detected in the acute phase and a preferential increase of CD8+ T cells with activated phenotypes was observed in both acute and convalescent phases. The remarkable decrease of CD4+ T cells, including Treg cells, during the acute phase of infection may contribute to the loss of immunological memory and generate helpless but unregulated cytotoxic T cell responses observed in vaccine studies and recurrent human infection.

Dendritic cell-based cancer immunotherapy requires tumour antigens to be delivered efficiently into dendritic cells and their migration to be monitored in vivo. Nanoparticles have been explored as carriers for antigen delivery, but applications have been limited by the toxicity of the solvents used to make nanoparticles, and by the need to use transfection agents to deliver nanoparticles into cells. Here we show that an iron oxide-zinc oxide core-shell nanoparticle can deliver carcinoembryonic antigen into dendritic cells while simultaneously acting as an imaging agent. The nanoparticle-antigen complex is efficiently taken up by dendritic cells within one hour and can be detected in vitro by confocal microscopy and in vivo by magnetic resonance imaging. Mice immunized with dendritic cells containing the nanoparticle-antigen complex showed enhanced tumour antigen specific T-cell responses, delayed tumour growth and better survival than controls.

Proteins localized within the same subcellular compartment tend to be functionally associated. This study shows that subcellular localization and network distance between disease-associated proteins provide complementary information explaining patterns of disease comorbidity., A positive correlation was found between subcellular localization of disease-associated protein pairs and measures of comorbidity. A higher comorbidity tendency was found for disease-associated protein pairs that are positioned within a shorter distance in the protein interaction network. The integration of subcellular localization information with protein interaction network sheds light onto the potential molecular connections underlying comorbidity patterns and will help to understand the mechanisms of human disease., It was shown that the emergence of phenotypically similar diseases are triggered as a result of molecular connections between disease-causing genes (Oti and Brunner, 2007; Zaghloul and Katsanis, 2010). From a genetics, perspective diseases are associated with certain genes (Goh et al, 2007; Feldman et al, 2008), whereas from a proteomics perspective phenotypically similar diseases are connected via biological modules such as protein–protein interactions (PPIs) or molecular pathways (Lage et al, 2007; Jiang et al, 2008; Wu et al, 2008; Linghu et al, 2009; Suthram et al, 2010). These molecular connections between diseases were observed on the population level as well: diseases connected through molecular connections such as shared genes, PPIs, and metabolic pathways tend to show elevated comorbidity (Rzhetsky et al, 2007; Lee et al, 2008; Zhernakova et al, 2009; Park et al, 2009a, 2009b). While these findings constitute a step toward improving our understanding of the mechanism of disease progression, there are still many more molecule-level connections between disease pairs that need to be explored in order to establish a firmer comorbidity association. Subcellular localization provides spatial information of proteins in the cell; proteins target subcellular localizations to interact with appropriate partners and form functional complexes in signaling pathways and metabolic processes (Au et al, 2007). Abnormal protein localizations are known to lead to the loss of functional effects in diseases (Luheshi et al, 2008; Laurila and Vihinen, 2009). For example, mis-localizations of nuclear/cytoplasmic transport have been detected in many types of carcinoma cells (Kau et al, 2004). A proper identification of protein subcellular localization can hence be useful in discovering disease-associated proteins (Giallourakis et al, 2005; Calvo and Mootha, 2010). With this understanding, we postulate that disease-associated proteins connected by subcellular localizations could also explain the phenotypic similarities between diseases. Furthermore, such connections may also couple to disease progressions that contribute to multiple disease manifestation, that is, comorbidity. Protein subcellular localization has been extensively studied through various methods to determine a variety of protein functions. To the best of our knowledge, the connection between diseases and subcellular localizations are yet to be studied systematically. To resolve this we constructed, for the first time, a human Disease-associated Protein and subcellular Localization (DPL) matrix (top panel in Box 1). Our DPL matrix provides the ‘cellular localization map of diseases' that represents the spatial index of diseases in the cell. We found that each disease shows unique characteristics of subcellular localization profile in the DPL matrix. We were interested in determining whether subsets of 1284 human diseases exhibit distinct enrichment profiles across subcellular localizations. We calculated pairwise correlations and performed a hierarchical clustering of the enrichments of the 1284 diseases across 10 different subcellular localizations. Our DPL matrix revealed that 778 diseases (∼62%, P=1.40 × 10−3) are enriched in a single localization and 273 diseases (∼21%, P=3.45 × 10−3) are enriched in dual localizations. In the DPL matrix, certain disease-associated proteins are likely to be found in membrane-bounded organelles such as mitochondria, lysosome, and peroxisome, indicating that the mutations of proteins localized to these compartments are connected to the pathophysiological conditions of those organelles. Meanwhile, certain disease-associated proteins in the DPL matrix are enriched in dual localizations, such as extracellular/plasma membrane or endoplasmic reticulum/Golgi. Although these two pairs of subcellular localizations appear to be distinct compartments at first, they are functionally related compartments in close proximity during protein translocation process in the cell, and thus are likely to share interacting protein partners (Gandhi et al, 2006). Comorbidity represents the co-occurrence of multiple diseases in the same individual (Lee et al, 2008; Hidalgo et al, 2009; Park et al, 2009a). Many comorbid disease pairs have been shown to share common genes in the human disease network. For example, Diabetes and Alzheimer's disease share a risk factor in angiotensin I converting enzyme, and frequently occur together in an individual. In such instances, comorbidity can be partially attributed to the disease connections on the molecular level. To explore the impact of protein subcellular localization on comorbidity, we hypothesized that certain disease pairs could also be connected via subcellular localization by the molecular connections between the disease-associated proteins (bottom panel in Box 1). We found a positive correlation between subcellular localization similarity and relative risk (Figure 3B, Pearson's correlation coefficient between relative risk and subcellular localization similarity=0.81, P=2.96 × 10−5). The subcellular localization similarity represents the correlation of subcellular localization profiles between disease pairs. To our surprise, when we compared the relative risk of disease pairs linked via various molecular connections, we found that disease pairs connected by subcellular localization showed a near three-fold higher comorbidity tendency (with link distances equal to 2 or 3) when compared with random pairs (Figure 3E). We then assessed quantitatively the impact of network distances and subcellular localizations on the comorbidity tendency of disease pairs. We expected the proteins associated with comorbid disease pairs to be located closely in the protein interaction network via fewer links compared with random disease pairs. Indeed, a higher comorbidity tendency was found when two disease-associated proteins were positioned within a shorter distance (gray plots in Figure 3F). Moreover, when subcellular localization information was combined with small network distances, the comorbidity tendency increased dramatically (orange plots in Figure 3F). It suggests that subcellular localization and close network distances, two conceptually distinct molecular connections, contributed synergistically to the comorbidity tendency. Disease progression is not restricted to the mutation of disease-causing genes, but also affected by molecular connections in ‘disease modules,' resulting in comorbidity (Fraser, 2006; Lee et al, 2008). In this study, for the first time we applied subcellular localization information to elucidate the molecular connections between comorbid diseases. We believe that, based on our finding, our approach helps to define the boundaries of ‘disease modules.' Taken together, integration of diverse molecular connections should improve the molecular level understanding of hitherto unexplained comorbid disease pairs and help us in expanding the scope of our knowledge of the mechanism of human disease progression., Proteins targeting the same subcellular localization tend to participate in mutual protein–protein interactions (PPIs) and are often functionally associated. Here, we investigated the relationship between disease-associated proteins and their subcellular localizations, based on the assumption that protein pairs associated with phenotypically similar diseases are more likely to be connected via subcellular localization. The spatial constraints from subcellular localization significantly strengthened the disease associations of the proteins connected by subcellular localizations. In particular, certain disease types were more prevalent in specific subcellular localizations. We analyzed the enrichment of disease phenotypes within subcellular localizations, and found that there exists a significant correlation between disease classes and subcellular localizations. Furthermore, we found that two diseases displayed high comorbidity when disease-associated proteins were connected via subcellular localization. We newly explained 7584 disease pairs by using the context of protein subcellular localization, which had not been identified using shared genes or PPIs only. Our result establishes a direct correlation between protein subcellular localization and disease association, and helps to understand the mechanism of human disease progression.

Bax inhibitor 1 (BI-1), a transmembrane protein with Ca2+ channel-like activity, has antiapoptotic and anticancer activities. Cells overexpressing BI-1 demonstrated increased cell adhesion. Using a proteomics tool, we found that BI-1 interacted with gamma-actin via leucines 221 and 225 and could control actin polymerization and cell adhesion. Among BI-1-/- cells and cells transfected with BI-1 small interfering RNA (siRNA), levels of actin polymerization and cell adhesion were lower than those among BI-1+/+ cells and cells transfected with nonspecific siRNA. BI-1 acts as a leaky Ca2+ channel, but mutations of the actin binding sites (L221A, L225A, and L221A/L225A) did not change intra-endoplasmic reticulum Ca2+, although deleting the C-terminal motif (EKDKKKEKK) did. However, store-operated Ca2+ entry (SOCE) is activated in cells expressing BI-1 but not in cells expressing actin binding site mutants, even those with the intact C-terminal motif. Consistently, actin polymerization and cell adhesion were inhibited among all the mutant cells. Compared to BI-1+/+ cells, BI-1-/- cells inhibited SOCE, actin polymerization, and cell adhesion. Endogenous BI-1 knockdown cells showed a similar pattern. The C-terminal peptide of BI-1 (LMMLILAMNRKDKKKEKK) polymerized actin even after the deletion of four or six charged C-terminal residues. This indicates that the actin binding site containing L221 to D231 of BI-1 is responsible for actin interaction and that the C-terminal motif has only a supporting role. The intact C-terminal peptide also bundled actin and increased cell adhesion. The results of experiments with whole recombinant BI-1 reconstituted in membranes also coincide well with the results obtained with peptides. In summary, BI-1 increased actin polymerization and cell adhesion through Ca2+ regulation and actin interaction.

In this study, Bax inhibitor-1 (BI-1) overexpression reduces the ER pool of Ca(2+) released by thapsigargin. Cells overexpressing BI-1 also showed lower intracellular Ca(2+) release induced by the Ca(2+) ionophore ionomycin as well as agonists of ryanodine receptors and inositol trisphosphate receptors. In contrast, cells expressing carboxyl-terminal deleted BI-1 (CDelta-BI-1 cells) displayed normal intracellular Ca(2+) mobilization. Basal Ca(2+) release rates from the ER were higher in BI-1-overexpressing cells than in control or CDelta-BI-1 cells. We determined that the carboxyl-terminal cytosolic region of BI-1 contains a lysine-rich motif (EKDKKKEKK) resembling the pH-sensing domains of ion channels. Acidic conditions triggered more extensive Ca(2+) release from ER microsomes from BI-1-overexpressing cells and BI-1-reconstituted liposomes. Acidic conditions also induced BI-1 protein oligomerization. Interestingly subjecting BI-1-overexpressing cells to acidic conditions induced more Bax recruitment to mitochondria, more cytochrome c release from mitochondria, and more cell death. These findings suggest that BI-1 increases Ca(2+) leak rates from the ER through a mechanism that is dependent on pH and on the carboxyl-terminal cytosolic region of the BI-1 protein. The findings also reveal a cell death-promoting phenotype for BI-1 that is manifested under low pH conditions.

Summary Background The hyper-sensitivity reaction of IgE, with its high-affinity receptors (FcɛRI), is central to the phenomenon of atopic diseases. Objective To evaluate the genetic effects of non-synonymous single-nucleotide polymorphisms (SNPs) of FcɛRI on intermediate phenotypes of asthma, i.e. atopy and airway hyper-responsiveness (AHR), in the Korean general population. Subjects and methods Atopy and AHR were evaluated in a cohort of 2055 subjects, aged 10–18 years, using skin prick tests (SPTs) for common aeroallergens and total serum IgE and methacholine bronchial provocation tests. All FcɛRI-α, FcɛRI-β, and FcɛRI-γ gene exons of 24 healthy subjects were sequenced to locate informative non-synonymous SNPs (minor allele frequency >2%). Informative SNPs were then scored, using the high-throughput single base extension method. Relative risk (RR) was determined by multiple logistic regression analysis, after adjusting for confounding factors. The functional relevance of non-synonymous SNPs was analysed using the sorting intolerant from tolerant (SIFT) program. Results The SNP search found only one informative non-synonymous SNP in FcɛRI-β: E237G (minor allele frequency=0.21). The positive rate of AHR was lower among subjects with the 237*E allele than among those with 237*G [RR (95% confidence interval)=0.41 (0.19–0.89); P=0.01]. However, the E237G substitution was not associated with either a positive SPT response or total serum IgE levels. Sequence evolution analysis predicted that the E237G variation is an intolerant amino acid substitution, with functional importance. Conclusion In the Korean general population, AHR is significantly associated with the E237G polymorphism of FcɛRI-β, which results in an intolerant amino acid substitution.

Complications associated with the use of bisphosphonate (BP) have risen over the years due to an increase in the prescription of BP. BP-related osteonecrosis of jaw (BRONJ), one of the complications linked to the consumption of BP, greatly affects patients with minor dental trauma, incurring a long healing period. While BRONJ afflicts only a minority of patients prescribed with BP, BRONJ is a multigenic disease affected both by environmental and genetic factors having a distinctive phenotype. This study aims to discover genetic biomarkers associated with BRONJ via whole exome sequencing (WES) followed by statistical analysis. Sixteen individuals who had been prescribed with bisphosphonate medication and diagnosed as BRONJ were chosen and each individual’s saliva sample was collected for WES. 126 randomized subsamples from the GSK project representing 109 male and 17 female Koreans were used as a control data set. Fisher’s exact test was carried out to assess the significance of genetic variants in BRONJ patients. Gene set enrichment analysis (GSEA) (DAVID Bioinformatics Resource 6.7) was used to perform a cluster analysis of variants found from Fisher‘s exact test. The results from this study suggest that BRONJ-inducing factors are genetically associated and BRONJ occurs due to the malfunctioning of post-translational modification in osteoclast leading to the impairment of cell morphology and adhesion.

We describe an effective procedure for modeling the structures of simple transmembrane helix homo-oligomers. The method differs from many previous approaches in that the only structural constraint we use to help select the correct model is the oligomerization state of the protein. The method involves the following steps: (1) perform 100-250 independent Monte Carlo energy minimizations of helix pairs to produce a large collection of well-packed structures; (2) filter the minimized structures to find those that are consistent with the expected symmetry of the oligomer; (3) cluster the structures that pass the symmetry filter; and (4) select a representative of the most populous cluster as the final prediction. We applied the method to the transmembrane helices of five proteins and compare our results to the available experimental data. Our predictions of glycophorin A, neu, the M2 channel and phospholamban resulted in a single model for each protein that agreed with the experimental results. In the case of erbB-2, however, we obtained three structurally distinct clusters of approximately equal sizes, so it was not possible to identify a clearly favored structure. This may reflect a real heterogeneity of packing modes for erbB-2, which is known to interact with different receptor subunits. Our method should be useful for obtaining structural models of transmembrane domains, improving our understanding of structure/function relationships for particular membrane proteins.

Background Aging is a fundamental biological process. Characterization of genetic and environmental factors that influence lifespan is a crucial step toward understanding the mechanisms of aging at the organism level. To capture the different effects of genetic and environmental factors on lifespan, appropriate statistical analyses are needed. Methodology/Principal Findings We developed an online application for survival analysis (OASIS) that helps conduct various novel statistical tasks involved in analyzing survival data in a user-friendly manner. OASIS provides standard survival analysis results including Kaplan-Meier estimates and mean/median survival time by taking censored survival data. OASIS also provides various statistical tests including comparison of mean survival time, overall survival curve, and survival rate at specific time point. To visualize survival data, OASIS generates survival and log cumulative hazard plots that enable researchers to easily interpret their experimental results. Furthermore, we provide statistical methods that can analyze variances among survival datasets. In addition, users can analyze proportional effects of risk factors on survival. Conclusions/Significance OASIS provides a platform that is essential to facilitate efficient statistical analyses of survival data in the field of aging research. Web application and a detailed description of algorithms are accessible from http://sbi.postech.ac.kr/oasis.

The mitochondrial protein repertoire varies depending on the cellular state. Protein component modifications caused by mitochondrial DNA (mtDNA) depletion are related to a wide range of human diseases; however, little is known about how nuclear-encoded mitochondrial proteins (mt proteome) changes under such dysfunctional states. In this study, we investigated the systemic alterations of mtDNA-depleted (ρ0) mitochondria by using network analysis of gene expression data. By modularizing the quantified proteomics data into protein functional networks, systemic properties of mitochondrial dysfunction were analyzed. We discovered that up-regulated and down-regulated proteins were organized into two predominant subnetworks that exhibited distinct biological processes. The down-regulated network modules are involved in typical mitochondrial functions, while up-regulated proteins are responsible for mtDNA repair and regulation of mt protein expression and transport. Furthermore, comparisons of proteome and transcriptome data revealed that ρ0 cells attempted to compensate for mtDNA depletion by modulating the coordinated expression/transport of mt proteins. Our results demonstrate that mt protein composition changed to remodel the functional organization of mitochondrial protein networks in response to dysfunctional cellular states. Human mt protein functional networks provide a framework for understanding how cells respond to mitochondrial dysfunctions., Author Summary Mitochondria are dynamic organelles that are essential for energy production and cellular processes in eukaryotic cells, and their functional failure is a major cause of age-associated degenerative diseases. To meet the specific needs of different cellular states, mitochondrial protein repertoires are adjusted. It is critical to characterize the systemic alterations of mitochondria to different cellular states to understand the dynamic organization of mitochondrial systems. In this study, we modularized the quantified proteomics data into protein functional networks to characterize gene expression changes under dysfunctional mitochondrial conditions. Our results demonstrate that mitochondrial protein repertoires changed to compensate for dysfunctional cellular states by reorganizing mitochondrial protein functional network. Through network clustering analysis, we discovered that cells respond to pathological conditions by modulating the coordinated expression/transport of mitochondrial proteins. Network analysis of mt proteins can advance our understanding of dysfunctional mitochondrial systems and elucidate the candidate mt proteins involved in human mitochondrial diseases.

Lipid rafts are membrane microdomains that function as platforms for signal transduction and membrane trafficking. Tyrosine kinase interacting protein (Tip) of T lymphotropic Herpesvirus saimiri (HVS) is targeted to lipid rafts in T cells and downregulates TCR and CD4 surface expression. Here, we report that the membrane-proximal amphipathic helix preceding Tip's transmembrane (TM) domain mediates lipid raft localization and membrane deformation. In turn, this motif directs Tip's lysosomal trafficking and selective TCR downregulation. The amphipathic helix binds to the negatively charged lipids and induces liposome tubulation, the TM domain mediates oligomerization, and cooperation of the membrane-proximal helix with the TM domain is sufficient for localization to lipid rafts and lysosomal compartments, especially the mutivesicular bodies. These findings suggest that the membrane-proximal amphipathic helix and TM domain provide HVS Tip with the unique ability to deform the cellular membranes in lipid rafts and to downregulate TCRs potentially through MVB formation., Author Summary Herpesvirus persists in its host by entering a latent state, periodically reactivating to produce infectious viral particles. Some of the herpesviruses have also been known to be related to cancers. Herpesvirus saimiri (HVS), an oncogenic monkey herpesvirus, persists in the T lymphocytes of its natural host, the squirrel monkey, without any apparent disease symptoms, but infection of other species of New World and Old World primates results in fulminant T cell lymphomas. Two viral oncoproteins, Saimiri Transforming Protein and Tyrosine kinase-interacting protein (Tip), are required for T cell transformation. It has been known that Tip may also play some role in viral persistency within T cells by inhibiting the activation of the host cells upon antigenic stimulation. Here, we have identified a structural domain, a putative amphipathic helical motif, preceding the transmembrane domain of Tip. We also found that the structural motif is essential for Tip's localization on specialized membrane domains, lipid rafts, and selective downregulation of antigen receptors. Furthermore, we could genetically dissect the functional roles of the amphipathic helical motif and transmembrane domain of Tip in membrane deformation and oligomerization, respectively. These findings significantly advanced our understanding of how herpesvirus modulates host lymphocytes for viral persistence and pathogenesis.

Background Amyloid precursor protein (APP) is enzymatically cleaved by γ-secretase to form two peptide products, either Aβ40 or the more neurotoxic Aβ42. The Aβ42/40 ratio is increased in many cases of familial Alzheimer's disease (FAD). The transmembrane domain (TM) of APP contains the known dimerization motif GXXXA. We have investigated the dimerization of both wild type and FAD mutant APP transmembrane domains. Results Using synthetic peptides derived from the APP-TM domain, we show that this segment is capable of forming stable transmembrane dimers. A model of a dimeric APP-TM domain reveals a putative dimerization interface, and interestingly, majority of FAD mutations in APP are localized to this interface region. We find that FAD-APP mutations destabilize the APP-TM dimer and increase the population of APP peptide monomers. Conclusion The dissociation constants are correlated to both the Aβ42/Aβ40 ratio and the mean age of disease onset in AD patients. We also show that these TM-peptides reduce Aβ production and Aβ42/Aβ40 ratios when added to HEK293 cells overexpressing the Swedish FAD mutation and γ-secretase components, potentially revealing a new class of γ-secretase inhibitors.